Policy-based scaling of computing resources in a networked computing environment

ABSTRACT

Embodiments of the present invention provide an approach for policy-driven (e.g., price-sensitive) scaling of computing resources in a networked computing environment (e.g., a cloud computing environment). In a typical embodiment, a workload request for a customer will be received and a set of computing resources available to process the workload request will be identified. It will then be determined whether the set of computing resources are sufficient to process the workload request. If the set of computing resources are under-allocated (or are over-allocated), a resource scaling policy may be accessed. The set of computing resources may then be scaled based on the resource scaling policy, so that the workload request can be efficiently processed while maintaining compliance with the resource scaling policy.

RELATED U.S. APPLICATION DATA

This patent document is a continuation of, and claims the benefit of,co-pending and co-owned U.S. patent application Ser. No. 15/903,624,filed Feb. 23, 2018, which is a continuation of commonly owned U.S.patent application Ser. No. 14/590,276, filed Jan. 6, 2015, issued Apr.10, 2018 as U.S. Pat. No. 9,940,595, which is a continuation of commonlyowned U.S. patent application Ser. No. 13/343,293, filed Apr. 4, 2012,issued Feb. 24, 2015 as U.S. Pat. No. 8,966,085. The entire contents ofeach of such applications are herein incorporated by reference.

TECHNICAL FIELD

In general, embodiments of the present invention relate to computingresource scaling. Specifically, embodiments of the present inventionrelate to policy-based (e.g., price sensitive) scaling of computingresource in a networked computing environment (e.g., a cloud computingenvironment).

BACKGROUND

The networked computing environment (e.g., cloud computing environment)is an enhancement to the predecessor grid environment, whereby multiplegrids and other computation resources may be further enhanced by one ormore additional abstraction layers (e.g., a cloud layer), thus makingdisparate devices appear to an end-consumer as a single pool of seamlessresources. These resources may include such things as physical orlogical computing engines, servers and devices, device memory, andstorage devices, among others.

Cloud-based resources may be widely used to support and operate manydifferent personal and/or business needs. Often, needs such aselasticity, high performance, and availability may be addressed by cloudsolution providers offering a system to scale customer's resources asneeded. Challenges may exist, however, in that current scalabilityfunctionality may either add or remove resources without consideringcustomer-specific policies and/or constraints.

SUMMARY

In general, embodiments of the present invention provide an approach forpolicy-driven (e.g., price-sensitive) scaling of computing resources ina networked computing environment (e.g., a cloud computing environment).In a typical embodiment, a workload request for a customer will bereceived and a set of computing resources available to process theworkload request will be identified. It will then be determined whetherthe set of computing resources are sufficient to process the workloadrequest. If the set of computing resources is under-allocated (or isover-allocated), a resource scaling policy may be accessed. The set ofcomputing resources may then be scaled based on the resource scalingpolicy, so that the workload request can be efficiently processed whilemaintaining compliance with the resource scaling policy.

A first aspect of the present invention provides a computer-implementedmethod for scaling computing resources in a networked computingenvironment, comprising: receiving a workload request in a computermemory medium for a customer; identifying a set of computing resourcesavailable in the network computing environment to process the workloadrequest; detecting a need to scale the set of computing resources basedon a comparison of the set of computing resources to a level ofcomputing resources needed to process the workload request; accessing aresource scaling policy associated with the customer; identifying a setof pricing criteria in the resource scaling policy; and scaling the setof computing resources to process the workload request based on the needand the set of pricing criteria.

A second aspect of the present invention provides a system for scalingcomputing resources in a networked computing environment, comprising: amemory medium comprising instructions; a bus coupled to the memorymedium; and a processor coupled to the bus that when executing theinstructions causes the system to: receive a workload request in acomputer memory medium for a customer; identify a set of computingresources available in the network computing environment to process theworkload request; detect a need to scale the set of computing resourcesbased on a comparison of the set of computing resources to a level ofcomputing resources needed to process the workload request; access aresource scaling policy associated with the customer; identify a set ofpricing criteria in the resource scaling policy; and scale the set ofcomputing resources to process the workload request based on the needand the set of pricing criteria.

A third aspect of the present invention provides a computer programproduct for scaling computing resources in a networked computingenvironment, the computer program product comprising a computer readablestorage media, and program instructions stored on the computer readablestorage media, to: receive a workload request in a computer memorymedium for a customer; identify a set of computing resources availablein the network computing environment to process the workload request;detect a need to scale the set of computing resources based on acomparison of the set of computing resources to a level of computingresources needed to process the workload request; access a resourcescaling policy associated with the customer; identify a set of pricingcriteria in the resource scaling policy; and scale the set of computingresources to process the workload request based on the need and the setof pricing criteria.

A fourth aspect of the present invention provides a method for deployinga system for scaling computing resources in a networked computingenvironment, comprising: providing a computer infrastructure beingoperable to: receive a workload request in a computer memory medium fora customer; identify a set of computing resources available in thenetwork computing environment to process the workload request; detect aneed to scale the set of computing resources based on a comparison ofthe set of computing resources to a level of computing resources neededto process the workload request; access a resource scaling policyassociated with the customer; identify a set of pricing criteria in theresource scaling policy; and scale the set of computing resources toprocess the workload request based on the need and the set of pricingcriteria.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of this invention will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings in which:

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 depicts a system diagram according to an embodiment of thepresent invention.

FIG. 5 depicts a diagram illustrating a computing resources scaling needaccording to an embodiment of the present invention.

FIG. 6 depicts a computing resource scaling option according to anembodiment of the present invention.

FIG. 7 depicts another computing resource scaling option according to anembodiment of the present invention.

FIG. 8 depicts a method flow diagram according to an embodiment of thepresent invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention, and therefore should not be considered aslimiting the scope of the invention. In the drawings, like numberingrepresents like elements.

DETAILED DESCRIPTION

Illustrative embodiments will now be described more fully herein withreference to the accompanying drawings, in which embodiments are shown.This disclosure may, however, be embodied in many different forms andshould not be construed as limited to the embodiments set forth herein.Rather, these embodiments are provided so that this disclosure will bethorough and complete and will fully convey the scope of this disclosureto those skilled in the art. In the description, details of well-knownfeatures and techniques may be omitted to avoid unnecessarily obscuringthe presented embodiments.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of this disclosure.As used herein, the singular forms “a”, “an”, and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. Furthermore, the use of the terms “a”, “an”, etc., do notdenote a limitation of quantity, but rather denote the presence of atleast one of the referenced items. The term “set” is intended to mean aquantity of at least one. It will be further understood that the terms“comprises” and/or “comprising”, or “includes” and/or “including”, whenused in this specification, specify the presence of stated features,regions, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,regions, integers, steps, operations, elements, components, and/orgroups thereof.

Embodiments of the present invention provide an approach forpolicy-driven (e.g., price-sensitive) scaling of computing resources ina networked computing environment (e.g., a cloud computing environment).In a typical embodiment, a workload request for a customer will bereceived and a set of computing resources available to process theworkload request will be identified. It will then be determined whetherthe set of computing resources are sufficient to process the workloadrequest. If the set of computing resources is under-allocated (or isover-allocated), a resource scaling policy may be accessed. The set ofcomputing resources may then be scaled based on the resource scalingpolicy, so that the workload request can be efficiently processed whilemaintaining compliance with the resource scaling policy.

It is understood in advance that although this disclosure includes adetailed description of cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded, automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active consumer accounts). Resource usage canbe monitored, controlled, and reported providing transparency for boththe provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited consumer-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10, there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM, or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

The embodiments of the invention may be implemented as a computerreadable signal medium, which may include a propagated data signal withcomputer readable program code embodied therein (e.g., in baseband or aspart of a carrier wave). Such a propagated signal may take any of avariety of forms including, but not limited to, electro-magnetic,optical, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that can communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium including, but not limited to, wireless,wireline, optical fiber cable, radio-frequency (RF), etc., or anysuitable combination of the foregoing.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a consumer to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via I/O interfaces22. Still yet, computer system/server 12 can communicate with one ormore networks such as a local area network (LAN), a general wide areanetwork (WAN), and/or a public network (e.g., the Internet) via networkadapter 20. As depicted, network adapter 20 communicates with the othercomponents of computer system/server 12 via bus 18. It should beunderstood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with computer system/server 12.Examples include, but are not limited to: microcode, device drivers,redundant processing units, external disk drive arrays, RAID systems,tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes. In oneexample, IBM® zSeries® systems and RISC (Reduced Instruction SetComputer) architecture based servers. In one example, IBM pSeries®systems, IBM System X® servers, IBM BladeCenter® systems, storagedevices, networks, and networking components. Examples of softwarecomponents include network application server software. In one example,IBM WebSphere® application server software and database software. In oneexample, IBM DB2® database software. (IBM, zSeries, pSeries, System x,BladeCenter, WebSphere, and DB2 are trademarks of International BusinessMachines Corporation registered in many jurisdictions worldwide.)

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.Consumer portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provides pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA. Further shown in management layer is computingresource scaling, which represents the functionality that is providedunder the embodiments of the present invention.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and consumer data storage and backup. As mentioned above,all of the foregoing examples described with respect to FIG. 3 areillustrative only, and the invention is not limited to these examples.

It is understood that all functions of the present invention asdescribed herein typically may be performed by the computing resourcescaling functionality (of management layer 64, which can be tangiblyembodied as modules of program code 42 of program/utility 40 (FIG. 1).However, this need not be the case. Rather, the functionality recitedherein could be carried out/implemented and/or enabled by any of thelayers 60-66 shown in FIG. 3.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments of the present invention are intended to be implemented withany type of networked computing environment now known or laterdeveloped.

Referring now to FIG. 4, a system diagram capable of implementing thefunctionality discussed herein according to an embodiment of the presentinvention is shown. It is understood that the teachings recited hereinmay be practiced within any type of networked computing environment 86(e.g., a cloud computing environment 50). A stand-alone computer system12 is shown in FIG. 4 for illustrative purposes only. In the event theteachings recited herein are practiced in a networked computingenvironment 86, each client need not have a computing resource scalingengine (engine 70). Rather, engine 70 could be loaded on a server orserver-capable device that communicates (e.g., wirelessly) with theclients to provide device protection therefor. Regardless, as depicted,engine 70 is shown within computer system/server 12. In general, engine70 can be implemented as program/utility 40 on computer system 12 ofFIG. 1 and can enable the functions recited herein. As further shown,engine 70 (in one embodiment) comprises a rules and/or computationalengine that processes a set (at least one) of rules 78 and/or providesconfidence-based computing resource allocation hereunder.

Along these lines, engine 70 may perform multiple functions similar to ageneral-purpose computer. Specifically, among other functions, engine 70may (among other things): receive a workload request 76 in a computermemory medium (e.g., 40 of FIG. 1) for a customer; identify a set ofcomputing resources 72 (e.g., in a pool 74 of computing resources)available in the network computing environment 86 to process theworkload request 76; detect a need to scale the set of computingresources based on a comparison of the set of computing resources to alevel of computing resources needed to process the workload request (viaengine 70 and rules 78 leveraging historical data or the like fromstorage device 82); access a resource scaling policy 80 associated withthe customer; identify a set of pricing criteria in the resource scalingpolicy; scale (the set of computing resources 72 to process the workloadrequest 76 based on the need and the set of pricing criteria; provisionadditional computing resources 88 to the set of computing resources 72(e.g., add to pool 74) based on the need without exceeding the pricingconstraint; de-provision computing resources from the set of computingresources to avoid exceeding the pricing constraint; and/or migrate dataamong the scaled set of computing resources.

Illustrative Example

Referring to FIG. 5, an illustrative example of one possible way toimplement the teachings recited herein is shown. As depicted, a workloadprocessing unit 100 communicates with storage devices 102A-B. It isassumed that workload processing unit 100 has been asked to process aset of workload requests. Under one embodiment of the present invention,the environment is monitored by engine 50 as indicated above. As such,the process may proceed as follows:

1. Engine 70 monitors customers resources

A. instances

B. storage

C. IP addresses

D. etc.

2. Engine 70 detects a need to scale existing resources

A. add resources

B. remove resources

3. Engine 70 looks up a policy of scalability for the customer.

4. If the policy has pricing considerations, the system determines thebest scaling approach.

A. resource size

-   -   1. x small=>y large (e.g., replace a number of small resources        with a larger resource)    -   2. y large=>x small (e.g., replace a single large resource with        a number of small resources)        5. Engine 70 requests any new resource(s).        6. Engine 70 migrates existing data from the old resource(s) to        the new resource(s).        7. Any old/unused resource(s) may be “cleaned up”

A. de-provisioned

B. stopped

C. removed

8. Engine 70 continues to monitor resource(s) for scalability concerns.

FIG. 6 depicts one possible solution in the event that storage units102A-B of FIG. 5 are insufficient to process an incoming workloadrequest. For example, assume that 25 GB of total storage are needed toprocess the incoming workload request while maintaining previousoperations. As depicted, engine 70 has provisioned an additional 10 GBstorage unit 102C for an additional cost of $10.00/month.

However, assume that upon further analysis, engine 70 determines thatthe collective cost of $30.00/month for three storage units 102A-C willexceed a pricing constraint of $27.00/month set forth in the associatedcustomer's resource scaling policy. In such an event, engine 70 willexamine other options. One such option is shown in FIG. 7. As depicted,instead of adding an additional storage unit to a pool of storage units,engine 70 has determined that utilizing a single larger 50 GB storageunit 104 at $25.00/month will provide the needed storage space while notexceeding the pricing constraint.

Referring now to FIG. 8, a method flow diagram according to anembodiment of the present invention is shown. As depicted, in step S1, aworkload request is received in a computer memory medium for a customer.In step S2, set of computing resources available in the networkcomputing environment to process the workload request is identified. Instep S3, a need to scale the set of computing resources is detectedbased on a comparison of the set of computing resources to a level ofcomputing resources needed to process the workload request. In step S4,a resource scaling policy associated with the customer is received. Instep S5, a set of pricing criteria is identified in the resource scalingpolicy. In step S6, the set of computing resources is scaled to processthe workload request based on the need and the set of pricing criteria.

While shown and described herein as a computing resource scalingsolution, it is understood that the invention further provides variousalternative embodiments. For example, in one embodiment, the inventionprovides a computer-readable/useable medium that includes computerprogram code to enable a computer infrastructure to provide computingresource scaling functionality as discussed herein. To this extent, thecomputer-readable/useable medium includes program code that implementseach of the various processes of the invention. It is understood thatthe terms computer-readable medium or computer-useable medium compriseone or more of any type of physical embodiment of the program code. Inparticular, the computer-readable/useable medium can comprise programcode embodied on one or more portable storage articles of manufacture(e.g., a compact disc, a magnetic disk, a tape, etc.), on one or moredata storage portions of a computing device, such as memory 28 (FIG. 1)and/or storage system 34 (FIG. 1) (e.g., a fixed disk, a read-onlymemory, a random access memory, a cache memory, etc.).

In another embodiment, the invention provides a method that performs theprocess of the invention on a subscription, advertising, and/or feebasis. That is, a service provider, such as a Solution Integrator, couldoffer to provide computing resource scaling functionality. In this case,the service provider can create, maintain, support, etc., a computerinfrastructure, such as computer system 12 (FIG. 1) that performs theprocesses of the invention for one or more consumers. In return, theservice provider can receive payment from the consumer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising content to one or morethird parties.

In still another embodiment, the invention provides acomputer-implemented method for computing resource scaling. In thiscase, a computer infrastructure, such as computer system 12 (FIG. 1),can be provided and one or more systems for performing the processes ofthe invention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system 12 (FIG. 1),from a computer-readable medium; (2) adding one or more computingdevices to the computer infrastructure; and (3) incorporating and/ormodifying one or more existing systems of the computer infrastructure toenable the computer infrastructure to perform the processes of theinvention.

As used herein, it is understood that the terms “program code” and“computer program code” are synonymous and mean any expression, in anylanguage, code, or notation, of a set of instructions intended to causea computing device having an information processing capability toperform a particular function either directly or after either or both ofthe following: (a) conversion to another language, code, or notation;and/or (b) reproduction in a different material form. To this extent,program code can be embodied as one or more of: an application/softwareprogram, component software/a library of functions, an operating system,a basic device system/driver for a particular computing device, and thelike.

A data processing system suitable for storing and/or executing programcode can be provided hereunder and can include at least one processorcommunicatively coupled, directly or indirectly, to memory elementsthrough a system bus. The memory elements can include, but are notlimited to, local memory employed during actual execution of the programcode, bulk storage, and cache memories that provide temporary storage ofat least some program code in order to reduce the number of times codemust be retrieved from bulk storage during execution. Input/outputand/or other external devices (including, but not limited to, keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening device controllers.

Network adapters also may be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems,remote printers, storage devices, and/or the like, through anycombination of intervening private or public networks. Illustrativenetwork adapters include, but are not limited to, modems, cable modems,and Ethernet cards.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed and, obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to aperson skilled in the art are intended to be included within the scopeof the invention as defined by the accompanying claims.

What is claimed is:
 1. A computer-implemented method for scalingcomputing resources in a networked computing environment, comprising:identifying a pool of computing resources available in the networkedcomputing environment to process a workload request, wherein the pool ofcomputer resources includes a pool of storage units; detecting a need toscale the pool of computing resources based on a comparison of the poolof computing resources to a level of computing resources needed toprocess a workload request; identifying a pricing constraint; andscaling the set of computing resources to process the workload requestbased on the level of computing resources needed and the pricingconstraint, wherein the scaling comprises: determining that replacingthe pool of storage units with a single storage unit larger than any ofthe storage units in the pool will not exceed the pricing constraint;de-provisioning the pool of storage units; and replacing the pool ofstorage units with the single storage unit larger than any of thestorage units in the pool.
 2. The computer-implemented method of claim1, further comprising determining the level of computing resourcesneeded to process the workload request.
 3. The computer-implementedmethod of claim 1, further comprising receiving the workload request fora customer.
 4. The computer-implemented method of claim 3, the scalingfurther comprising provisioning additional computing resources to thepool of computing resources based on the level of computing resourcesneeded without exceeding the pricing constraint.
 5. Thecomputer-implemented method of claim 1, further comprising migratingdata among the scaled set of computing resources.
 6. Thecomputer-implemented method of claim 1, the networked computingenvironment comprising a cloud computing environment.
 7. The method ofclaim 1, wherein a service solution provider provides a computerinfrastructure that performs the method for one or more consumers.
 8. Asystem for scaling computing resources in a networked computingenvironment, comprising: a memory medium comprising instructions; a buscoupled to the memory medium; and a processor coupled to the bus thatwhen executing the instructions causes the system to: identifying a poolof computing resources available in the networked computing environmentto process a workload request, wherein the pool of computer resourcesincludes a pool of storage units; detecting a need to scale the pool ofcomputing resources based on a comparison of the pool of computingresources to a level of computing resources needed to process a workloadrequest; identifying a pricing constraint; and scaling the set ofcomputing resources to process the workload request based on the levelof computing resources needed and the pricing constraint, wherein thescaling comprises: determining that replacing the pool of storage unitswith a single storage unit larger than any of the storage units in thepool will not exceed the pricing constraint; de-provisioning the pool ofstorage units; and replacing the pool of storage units with the singlestorage unit larger than any of the storage units in the pool.
 9. Thesystem of claim 8, the memory medium further comprising instructions forcausing the system to determine the level of computing resources neededto process the workload request.
 10. The system of claim 8, the memorymedium further comprising instructions for receiving the workloadrequest for a customer.
 11. The system of claim 10, the memory mediumfurther comprising instructions for causing the system to provisionadditional computing resources to the pool of computing resources basedon the level of computing resources needed without exceeding the pricingconstraint.
 12. The system of claim 8, the memory medium furthercomprising instructions for causing the system to migrate data among thescaled set of computing resources.
 13. The system of claim 8, thenetworked computing environment comprising a cloud computingenvironment.
 14. A computer program product for scaling computingresources in a networked computing environment, the computer programproduct comprising a computer readable hardware storage device andprogram instructions stored on the computer readable storage media, to:identifying a pool of computing resources available in the networkedcomputing environment to process a workload request, wherein the pool ofcomputer resources includes a pool of storage units; detecting a need toscale the pool of computing resources based on a comparison of the poolof computing resources to a level of computing resources needed toprocess a workload request; identifying a pricing constraint; andscaling the set of computing resources to process the workload requestbased on the level of computing resources needed and the pricingconstraint, wherein the scaling comprises: determining that replacingthe pool of storage units with a single storage unit larger than any ofthe storage units in the pool will not exceed the pricing constraint;de-provisioning the pool of storage units; and replacing the pool ofstorage units with the single storage unit larger than any of thestorage units in the pool.
 15. The computer program product of claim 14,the computer readable hardware storage device further comprisinginstructions to determine the level of computing resources needed toprocess the workload request.
 16. The computer program product of claim14, the computer readable hardware storage device further comprisinginstructions to receive the workload request for a customer.
 17. Thecomputer program product of claim 14, the computer readable hardwarestorage device further comprising instructions to migrate data among thescaled set of computing resources.